Dealing on the more recondite aspects of healthcare creeping into our doorsteps. Like how research into chemical weapons protection can also help us "civilians".

Sunday, October 25, 2015

Artificial Intelligence Programs: The New Cancer Treatment Paradigm?

Even though it can’t yet pass the Turing Test, does Berg
Health’s artificial intelligent computer program represent a new paradigm in cancer
treatment research and development?

By: Ringo Bones

Even though the working principles of such computer programs
were first mentioned in Star Trek: The Next Generation and other science
fiction programs back in the late 1980s, it is only relatively recently that an
artificial intelligent computer program had actually reduced the time and costs
in the research and development of new anti-cancer drugs - which is of upmost importance
if the new anti-cancer drug proves to be safer than current chemotherapy and
radiotherapy treatment schemes. Even though it can’t yet pass the Turing Test,
it does show promise of reducing the excessive costs and lengthy development
times in introducing new and more effective anti-cancer treatment drugs to the
market.

Berg Health – a pharmaceutical start up founded in back in 2008
with Silicon Valley venture capital backing, said that its proprietary
artificial intelligent computer program has managed to slash both time and
development costs of putting a new more effective anti-cancer drug into the
market. It has already managed to develop a new anti-cancer drug that’s expected
to go on sale within three years – marking seven years in development compared
to the general 14 years using previous methods.

Recent cancer research shows that healthy cells feed on
glucose in the body and then die off in a process known as cell death when
their usefulness draws to a close. But in some circumstances the mitochondria –
the part of the cell that provides its energy – malfunctions and metabolizes
lactic acid instead of glucose, turning off the built in cell death function at
the same time. The cell can then become cancerous and a tumor grows. Berg
Health’s new drug – BPM31510 – will reactivate the mitochondria, restarting the
metabolizing of glucose as normal and reinstituting call death so the body can
harmlessly pass the problem cell out of the body.

Berg Health’s research and development team used a
specialized form of artificial intelligence computer program to compare samples
taken from patients with the most aggressive strains of cancer, including
pancreatic, bladder and brain, with those from non-cancerous individuals. The
technology highlighted disparities between the corresponding biological
profiles, selecting those it predicted would respond best to the drug being
tested.

“We’re looking at 14-trillion data points in a single tissue
sample. We can’t humanly process that”, says Niven Narain, a clinical oncologist
and Berg Health co founder. “Because we’re tackling this data-driven approach,
we need a supercomputer capability. We use them for mathematics in a big data
analytic platform, so it can collate that data into various categories: healthy
population for women, for men, disease candidates, etc, and it’s able to take
these slices in time and integrate them so that we’re able to see where it’s
gone wrong and develop drugs based on that information,” Mr. Narain said.

Berg Health expects to begin phase two trials of the drug in
January 2016, meaning it has already been proven to be effective on animal or
cell culture tests and is safe to continue testing in humans. Mr. Narain said
it usually takes 2.6-billion US dollars and 12 to 14 years to get a new drug to
the market, and that the trial metric within four and a half years worth of
development indicated the time it takes to create a new drug can be cut by at
least 50-percent. This will also translate into less expenditure, he claimed. “I
don’t believe we’re going to spend 1.3-billion US dollars to produce our first
drug, so the cost is cut by at least 50-percent too” he added. “There’s a bit
of trial and error in the old model so a lot of these costs are due to the
failure of really expensive clinical trials. We’re able to be more predictive
and effective…and that’s going to cut hundreds of millions of dollars off the
cost.”